Voxelwise genome-wide association study (vGWAS)

Abstract

The structure of the human brain is highly heritable, and is thought to be influenced by many common genetic variants, many of which are currently unknown. Recent advances in neuroimaging and genetics have allowed collection of both highly detailed structural brain scans and genome-wide genotype information. This wealth of information presents a new opportunity to find the genes influencing brain structure. Here we explore the relation between 448,293 single nucleotide polymorphisms in each of 31,622 voxels of the entire brain across 740 elderly subjects (mean age±s.d.: 75.52±6.82 years; 438 male) including subjects with Alzheimer's disease, Mild Cognitive Impairment, and healthy elderly controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used tensor-based morphometry to measure individual differences in brain structure at the voxel level relative to a study-specific template based on healthy elderly subjects. We then conducted a genome-wide association at each voxel to identify genetic variants of interest. By studying only the most associated variant at each voxel, we developed a novel method to address the multiple comparisons problem and computational burden associated with the unprecedented amount of data. No variant survived the strict significance criterion, but several genes worthy of further exploration were identified, including CSMD2 and CADPS2. These genes have high relevance to brain structure. This is the first voxelwise genome wide association study to our knowledge, and offers a novel method to discover genetic influences on brain structure.

An Overview of Genome-Wide Association Studies in Alzheimer’s Disease

“…The well-replicated association of CR1 and PICALM among AD cases and controls has also been confirmed in a multi-center GWAS using phenotypes of AD-related neuroimaging changes such as hippocampal volume [49]. Stein et al [50] conducted the first voxel-wise GWAS and suggested CSMD2 and CADPS2 as candidate genes for future investigation. Ramanan et al [51] used florbetapir ( 18 F) positron emission tomography (PET) to evaluate the cortical load of amyloid b, which revealed an association of APOE and BCHE with this load.…”

Genetics of the Connectome and the ENIGMA Project

“…Although it may seem a daunting task, Stein et al (2010) proposed a method to screen every voxel (location) in the brain and every genotyped variant in a genomic screen to search both images and genomes at once for promising associations. The sheer number of computations can exceed one billion statistical tests.…”

Micro-, Meso- and Macro-Connectomics of the Brain

“…Around 2009, GWAS began to be performed on brain measures [see supplementary information in Medland et al (2014)], such as temporal lobe volume (Stein et al 2010). Although some of the top "hits" in these studies seemed convincing from a mechanistic point of view, many geneticists argued that the power to detect common genetic variants that affect the brain was very limited, even in samples of approximately 1000 subjects.…”

“…Pilot studies showed that the data could be analyzed in a consistent way (Jahanshad et al 2013a;Kochunov et al 2014). As the ENIGMA3 project involves a cortical volumetric analysis, the current plan is for ENIGMA to use those cortical regions as the basis for a structural connectivity analysis, using the same voxel-wise analysis of the connections as advocated in Stein et al (2010) and Jahanshad et al (2013b). It will be interesting to see if similar sample sizes, tens of thousands, are needed to find and replicate genetic associations with measures of structural brain connectivity.…”